store = {}
store['args']={'batch_size': 64, 'scoring_batch_size': 512, 'test_batch_size': 512, 'validation_set_size': 1024, 'early_stopping_patience': 3, 'epochs': 30, 'epoch_samples': 5056, 'num_inference_samples': 20, 'available_sample_k': 40, 'num_iterations': 20, 'no_cuda': False, 'name': 'bald_40_527608', 'seed': 527608, 'log_interval': 20, 'type': 'AcquisitionFunction.bald'}
store['iterations']=[]
store['initial_samples']=[33253, 689, 35990, 24974, 5236, 24552, 11301, 24386, 20346, 54672, 43799, 22920, 3366, 9946, 51591, 44640, 33979, 43403, 36991, 26861]
store['iterations'].append({'num_epochs': 4, 'test_metrics': {'accuracy': 0.6586, 'nll': 2.4625169986724855}, 'chosen_samples': [40939, 10663, 26376, 46317, 5787, 38167, 38719, 10856, 14484, 26901, 27269, 54904, 27995, 50096, 27195, 38687, 23861, 50957, 58758, 20133, 38399, 42656, 36870, 39461, 10578, 26136, 20120, 49756, 27121, 48606, 20254, 34629, 49656, 45540, 21963, 39473, 39124, 1199, 19609, 54867], 'chosen_samples_score': ['1.0902507', '1.0951413', '1.0948348', '1.0906136', '1.0955961', '1.1295158', '1.1218202', '1.2115543', '1.166986', '1.1126409', '1.2070789', '1.206569', '1.1259236', '1.1167457', '1.1303437', '1.1411457', '1.116416', '1.1087046', '1.1499838', '1.1832048', '1.1006246', '1.2328308', '1.1289883', '1.2164924', '1.104081', '1.1140175', '1.1238966', '1.2537541', '1.1167817', '1.1632049', '1.1414295', '1.1295955', '1.283489', '1.1901541', '1.1336954', '1.1583507', '1.1112857', '1.1195045', '1.3128684', '1.1385638']})
store['iterations'].append({'num_epochs': 4, 'test_metrics': {'accuracy': 0.6733, 'nll': 1.766433776473999}, 'chosen_samples': [48328, 55797, 38760, 14051, 29441, 23086, 10017, 59853, 40157, 36155, 26737, 11173, 55302, 47761, 28440, 13538, 8805, 53463, 22944, 50837, 8484, 50086, 32640, 40501, 55731, 49353, 50500, 19503, 21407, 56643, 13062, 16064, 13261, 17756, 55128, 19451, 39495, 42513, 10234, 42723], 'chosen_samples_score': ['0.8855043', '0.8857808', '0.8903984', '0.88702166', '0.8910312', '0.89175785', '0.88882625', '0.8925578', '0.8863013', '0.89193594', '0.8939809', '0.9229621', '0.94250554', '0.90369725', '0.94537896', '0.9897738', '0.90746194', '0.9341917', '0.9046372', '0.9144364', '0.9812072', '0.97350055', '0.9115807', '0.91790265', '0.90027887', '0.9063288', '0.9435124', '0.8963032', '0.92072314', '0.8996324', '0.93706596', '0.8975937', '0.92532295', '0.94865066', '0.9073081', '0.99289197', '0.937602', '0.911981', '0.90335715', '0.89949715']})
store['iterations'].append({'num_epochs': 5, 'test_metrics': {'accuracy': 0.8205, 'nll': 1.028782524871826}, 'chosen_samples': [37976, 15593, 2553, 1239, 35018, 4687, 20169, 17978, 3371, 8339, 33461, 30011, 58076, 29335, 36587, 32343, 21245, 30378, 6518, 13893, 11300, 56078, 32331, 33249, 3644, 9437, 33041, 12514, 24704, 20861, 20700, 36186, 9481, 58469, 42796, 37111, 14015, 40601, 52358, 30418], 'chosen_samples_score': ['0.9326524', '0.939691', '0.94529957', '0.94349134', '0.93992066', '0.9478181', '0.9500888', '0.95449215', '0.95481193', '0.96828514', '0.9548015', '0.956866', '0.9736387', '0.9749656', '0.96655864', '0.96265054', '0.9739725', '0.97576416', '0.97709286', '0.9798053', '1.0687666', '0.98688763', '0.9838521', '1.0032432', '0.99105144', '1.0725453', '1.036039', '0.99910843', '1.0217285', '0.99070203', '1.0046365', '1.0115377', '1.0556984', '1.0188326', '0.98503906', '1.0902786', '1.0108244', '0.99366033', '1.1480932', '1.0618124']})
store['iterations'].append({'num_epochs': 5, 'test_metrics': {'accuracy': 0.8361, 'nll': 0.9252472679138184}, 'chosen_samples': [40066, 25048, 1149, 14367, 18029, 42632, 35225, 33753, 36283, 33082, 49537, 59913, 2659, 21396, 49493, 59343, 7168, 34551, 35645, 33571, 27703, 49692, 38892, 54155, 43176, 25281, 57473, 17483, 19855, 48854, 3942, 51986, 32126, 39363, 4216, 20547, 11364, 34429, 41881, 21393], 'chosen_samples_score': ['0.8546722', '0.8550093', '0.85795254', '0.858566', '0.8955057', '0.8966592', '0.9128025', '0.901917', '0.8688224', '0.8777242', '0.8802089', '0.8735917', '0.86989796', '0.87156296', '0.9125787', '0.8708973', '0.9303331', '0.868401', '0.9111584', '0.8654348', '0.858599', '0.8771395', '0.8728886', '0.9165265', '0.91895634', '0.9107233', '0.861065', '0.89890295', '0.86716413', '0.8590521', '0.9647223', '0.88814676', '0.9378411', '1.0334507', '0.86588466', '0.87475175', '0.9396039', '0.9349742', '0.8767325', '0.99965554']})
store['iterations'].append({'num_epochs': 6, 'test_metrics': {'accuracy': 0.9202, 'nll': 0.5568045189857483}, 'chosen_samples': [14193, 1674, 45380, 17934, 12524, 28373, 31090, 21040, 54099, 5740, 36363, 39304, 50905, 32466, 32926, 23187, 10400, 24408, 39656, 20171, 47698, 14765, 44212, 47613, 3030, 23806, 36942, 59314, 36409, 14290, 43126, 39320, 46892, 32880, 2856, 31626, 51492, 31664, 22670, 20418], 'chosen_samples_score': ['0.89772373', '0.8982991', '0.8996027', '0.90070635', '0.90202963', '0.94364935', '0.9258308', '0.90613836', '0.91821975', '0.94104064', '0.9416407', '0.9204987', '0.9142116', '0.9101008', '0.93073845', '0.94019866', '0.9459605', '0.92261904', '0.90394765', '0.91552687', '0.937034', '0.94942033', '0.9053785', '0.92236656', '0.91116446', '0.91773456', '0.9069527', '0.9325624', '0.95115095', '0.9539159', '0.95624894', '0.95818293', '0.9761989', '0.96775925', '0.957534', '0.9538241', '0.99862844', '1.0064194', '1.0041559', '1.0109744']})
store['iterations'].append({'num_epochs': 8, 'test_metrics': {'accuracy': 0.9416, 'nll': 0.4302424627304077}, 'chosen_samples': [15987, 36744, 51842, 43256, 22561, 49109, 18322, 36417, 10194, 50461, 37307, 49506, 33110, 59468, 57732, 59563, 20322, 26538, 6347, 12986, 39335, 32250, 12188, 32269, 4955, 17050, 7033, 13709, 38688, 42139, 11708, 23094, 32445, 1652, 52661, 46379, 22801, 27503, 11729, 16011], 'chosen_samples_score': ['0.8997924', '0.8999068', '0.9041329', '0.9009083', '0.90987766', '0.91013736', '0.9118466', '0.9225685', '0.9512774', '0.93157315', '0.9319945', '0.9336918', '0.93414974', '0.958823', '0.9157946', '0.9150662', '0.94487786', '0.9225121', '0.9172254', '0.9254573', '0.92836577', '0.9131734', '0.9316689', '0.96185136', '0.97226274', '0.98505455', '1.1191282', '1.0013113', '1.0101902', '0.9674044', '1.02775', '0.9844156', '0.9758196', '1.0229394', '0.96190476', '1.0506667', '0.99250543', '1.0065856', '0.96459144', '1.0153792']})
store['iterations'].append({'num_epochs': 7, 'test_metrics': {'accuracy': 0.9441, 'nll': 0.39671978368759153}, 'chosen_samples': [43532, 11304, 37305, 44245, 2803, 25482, 13983, 43626, 48360, 17603, 56454, 41487, 17505, 37696, 44131, 8761, 49395, 8867, 23059, 52582, 24513, 34122, 45502, 7631, 39429, 39411, 13985, 20292, 26079, 20859, 42892, 58390, 4185, 30047, 41133, 26405, 13259, 12305, 36704, 1448], 'chosen_samples_score': ['0.8581563', '0.8601776', '0.8590559', '0.8609388', '0.8634388', '0.8643675', '0.86487395', '0.86925334', '0.87198037', '0.87546295', '0.90215456', '0.95610434', '0.94836223', '1.0394633', '0.90865815', '0.9780366', '0.9552206', '0.89402604', '0.92524487', '0.8961616', '0.9809123', '0.9631708', '0.93493396', '0.93096465', '0.8744494', '0.8926088', '0.93447876', '0.8826518', '0.8836737', '0.9263606', '0.91759044', '0.911405', '0.9284823', '0.9917593', '0.9135508', '0.90113544', '0.9950082', '0.9708099', '0.9419787', '0.8900951']})
store['iterations'].append({'num_epochs': 10, 'test_metrics': {'accuracy': 0.9541, 'nll': 0.36019655389785765}, 'chosen_samples': [52012, 46412, 50308, 42787, 39356, 7768, 15781, 47651, 18398, 25508, 49091, 3336, 49824, 29672, 1477, 31301, 49064, 8719, 10210, 30884, 57956, 35248, 42415, 54030, 26358, 21426, 38698, 5370, 28512, 11572, 19502, 37044, 2000, 24479, 13969, 5679, 17079, 59289, 46441, 11482], 'chosen_samples_score': ['0.88243043', '0.88782656', '0.88601726', '0.88399404', '0.88420475', '0.8917926', '0.89779484', '0.9008234', '0.91369534', '0.9358409', '0.93290883', '0.9563363', '0.91622704', '0.92148423', '0.90104127', '0.90206075', '0.9333937', '0.9144082', '0.90241516', '0.93717474', '0.90540195', '0.9042842', '0.90995514', '0.9015354', '0.9750611', '0.9213319', '0.9421197', '0.91391957', '0.98099273', '1.0627205', '1.0056274', '0.99800605', '1.0145661', '1.0430286', '1.1005068', '1.0653663', '1.0275154', '1.0229498', '1.0254729', '1.0841446']})
store['iterations'].append({'num_epochs': 10, 'test_metrics': {'accuracy': 0.9531, 'nll': 0.35030561842918395}, 'chosen_samples': [37508, 36421, 24560, 5052, 33338, 46368, 52462, 17592, 14355, 52978, 41295, 2548, 39778, 20206, 19344, 1075, 11696, 38374, 34942, 39526, 31677, 50317, 4355, 44746, 20903, 44123, 42702, 18003, 14333, 45439, 49573, 8116, 21358, 22364, 54885, 30856, 22083, 47655, 20746, 54986], 'chosen_samples_score': ['0.8763666', '0.87709534', '0.8799426', '0.87848854', '0.8811041', '0.9369081', '0.984212', '0.8908496', '0.8993546', '0.88636744', '0.9625285', '0.892644', '0.8829331', '0.90160567', '0.99298954', '1.0671971', '0.8988768', '0.89003706', '0.8970994', '0.8979413', '0.8947488', '0.88577914', '0.9664627', '1.1150455', '1.0205939', '0.95463836', '0.8839267', '0.9480994', '0.90519196', '0.90233266', '0.9776782', '0.9564304', '0.9501204', '0.923427', '0.9549321', '0.90665597', '1.0120531', '0.92281026', '0.88957083', '0.884995']})
store['iterations'].append({'num_epochs': 9, 'test_metrics': {'accuracy': 0.9582, 'nll': 0.343149320268631}, 'chosen_samples': [45761, 38347, 24031, 29003, 33505, 41371, 30155, 21700, 44090, 47723, 11292, 51261, 48630, 45901, 42337, 37360, 54908, 27700, 28368, 2450, 15579, 23028, 28491, 9448, 18810, 23814, 52686, 52089, 340, 39146, 59286, 51848, 40240, 34078, 41078, 32276, 38064, 14152, 8853, 31512], 'chosen_samples_score': ['0.8545134', '0.8554152', '0.8557793', '0.8559795', '0.8564922', '0.8586719', '0.85760134', '0.8599565', '0.8793886', '0.94483286', '0.8717751', '0.86194354', '0.8992927', '0.90754426', '0.9401132', '0.86358786', '0.9486224', '0.9829805', '0.95397484', '0.8929075', '0.8870605', '1.1813153', '0.93929935', '0.9259432', '0.87021446', '0.91084266', '0.9167662', '0.8935249', '0.88607246', '0.87573385', '0.87608296', '0.92589104', '0.8947743', '0.8766221', '0.9019206', '0.8909582', '0.9395286', '0.9258704', '0.86743903', '0.8982826']})
store['iterations'].append({'num_epochs': 11, 'test_metrics': {'accuracy': 0.9606, 'nll': 0.3086201865673065}, 'chosen_samples': [20869, 41464, 25748, 50231, 48899, 23386, 28152, 51130, 18487, 51180, 31293, 5684, 20792, 30255, 55739, 31690, 36152, 50370, 16488, 57718, 31738, 56218, 53872, 14697, 31558, 16882, 45446, 18501, 5896, 10744, 46132, 4784, 46356, 58036, 10736, 2034, 30457, 13876, 11074, 41426], 'chosen_samples_score': ['0.8887279', '0.8889765', '0.88937134', '0.8898279', '0.89080554', '0.8898968', '0.8924824', '0.89335036', '0.8949221', '0.8961289', '0.8964147', '0.9571402', '0.91455996', '0.946273', '1.0028414', '0.9038903', '1.054096', '0.89824927', '0.9141106', '0.9301721', '0.89811957', '1.0308588', '1.018391', '0.9690926', '0.9098896', '0.9910518', '0.91131604', '0.95697933', '0.9818658', '0.9848357', '0.9904305', '1.0997055', '0.95865905', '1.004962', '1.1659522', '0.89912665', '0.91282576', '0.99746007', '0.95872587', '0.9082191']})
store['iterations'].append({'num_epochs': 15, 'test_metrics': {'accuracy': 0.9681, 'nll': 0.2977614208221436}, 'chosen_samples': [916, 38065, 58832, 9554, 18654, 49012, 29180, 1568, 3762, 33892, 25803, 22692, 57628, 25159, 51764, 35401, 36669, 49488, 12891, 56914, 35406, 37023, 26756, 56773, 2580, 23956, 45602, 2148, 37062, 37469, 28844, 3810, 48681, 7308, 846, 17005, 24587, 8202, 23674, 40466], 'chosen_samples_score': ['0.92096174', '0.9217649', '0.9282502', '0.9229575', '0.9246076', '0.9273996', '0.92586607', '0.9304394', '0.93162906', '0.93173224', '0.9389149', '0.9382422', '0.93586504', '0.93922496', '0.9487562', '0.93955636', '0.9429892', '0.9591826', '0.9438933', '0.95464605', '0.9717279', '0.973847', '0.9749385', '1.0506401', '1.0113442', '1.1742333', '1.0508672', '1.0972717', '0.99741733', '1.0166517', '0.98038536', '0.97765493', '1.014292', '1.0826308', '1.0328606', '0.9796518', '0.99024606', '1.0123208', '1.0605822', '1.0321864']})
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store['iterations'].append({'num_epochs': 14, 'test_metrics': {'accuracy': 0.9735, 'nll': 0.2581421953201294}, 'chosen_samples': [14201, 43519, 34478, 54950, 29767, 1160, 25246, 44753, 7726, 46367, 26444, 20641, 52694, 52168, 43897, 36452, 42989, 17382, 32850, 10044, 7440, 48649, 43560, 50274, 29530, 32206, 14722, 36078, 8093, 21601, 54880, 46432, 54892, 4153, 51863, 49957, 33812, 35654, 32776, 52914], 'chosen_samples_score': ['0.8411913', '0.84842026', '0.8480167', '0.8444254', '0.8455645', '0.84305215', '0.8519833', '0.8604939', '0.853431', '0.85310274', '0.8577034', '0.8597292', '0.8662823', '0.8913561', '0.8958016', '0.87092865', '0.87350243', '0.88502127', '0.8839161', '0.887292', '0.86886376', '0.87900156', '0.8976487', '0.87557846', '0.90791255', '0.9039962', '0.91304445', '0.9220332', '0.9624925', '0.9468273', '1.0138223', '0.91835254', '0.94496405', '1.0133598', '0.9155547', '0.92609555', '1.0795814', '0.9472827', '0.9884983', '0.92898834']})
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